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4 recordsLinked to original sources

PubMed2026

Multi-omics characterization of flavor profile differences in the Longissimus thoracis between Angus and Hereford cattle.

BACKGROUND: Angus and Hereford cattle are premier breeds widely used in genetic improvement and crossbreeding programs to enhance meat quality, yet the flavor differences between them remain poorly understood. RESULTS: In this study, we performed an integrated analysis using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS)-based volatile metabolomics, lipidomics, and untargeted metabolomics to characterize the flavor profiles of the Longissimus thoracis (LT) muscle from both breeds and to identify potential precursor substances underlying flavor formation. In total, we identified 76 differential volatile organic compounds (VOCs) among the 493 candidate VOCs. By combing relative odor activity value (ROAV) and sensory attribute annotation, 2,3-butanedione which may contribute to the creamy aroma was revealed as the core differential VOC between the two breeds. This finding was robustly validated across SHAP (Shapley additive explanations) analysis, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment, and flavor annotation. Lipidomic analysis revealed 689 differential lipids primarily belonging to classes such as phosphatidylcholine, triglycerides, and phosphatidylethanolamine. Correlation analysis further linked these lipid profiles to flavor, showing that fatty acids (FAs) including FA(19:0), FA(18:2 + O), FA(14:1), FA(16:1), and FA(14:0) were significantly correlated with 2,3-butanedione. Notably, the unsaturated fatty acids (UFAs) in the Longissimus thoracis (LT) of Hereford cattle exhibited higher double bond content compared to Angus cattle, suggesting a greater potential for rich flavor development. Untargeted metabolomics revealed that nine of the 9474 metabolites were significantly correlated with both 2,3-butanedione and FAs, including norepinephrine, l-beta-aspartyl-l-leucine, and artemetin. CONCLUSIONS: Overall, our research has identified differential flavor compounds and potential precursor substances between Angus cattle and Hereford cattle, providing targeted guidance for breed improvement. © 2026 Society of Chemical Industry.

2,3‐butanedione↗

PubMed2026

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide↗

PubMed2026

Integrated electronic nose, GC-MS, and metagenomic analyses reveal volatile flavor and microbial community differences in heap-fermented grains of Jiangxiangxing Baijiu across different fermentation degrees.

The fermentation degree of heap-fermented grains in Jiangxiangxing Baijiu production is a critical factor influencing base Baijiu quality. However, conventional assessment methods largely rely on empirical experience and therefore suffer from limited objectivity and accuracy. In this study, integrated volatile profiling and metagenomic approaches were employed to investigate volatile characteristics and microbial functional potential differentiation in fermented grains with different fermentation degrees (under-fermented, normally fermented, and over-fermented). Significant differences in physicochemical properties were observed among fermentation degrees, particularly in acidity and reducing sugar content. Electronic nose analysis revealed distinct sensor response patterns among different fermentation degrees, indicating differences in overall volatile odor fingerprint patterns. A total of 81 volatile compounds were identified by HS-SPME-GC-MS, with aldehydes, ketones, and pyrazines showing pronounced variations among fermentation degrees, and acetaldehyde exhibiting strong discriminatory potential. LEfSe analysis identified 18 microbial taxa as potential biomarkers associated with different fermentation degrees, including Pichia kudriavzevii, Lentibacillus daiqui, and Acetobacter pasteurianus. Correlation analysis revealed significant positive associations between acetaldehyde levels and Acetobacter abundance. Furthermore, KEGG, CAZy, and eggNOG analyses revealed differentiated functional potentials among fermentation degrees, providing insights into the potential metabolic basis associated with flavor differentiation. Overall, these findings highlight that fermentation degree differentiation is closely associated with coordinated changes in physicochemical conditions, microbial communities, and functional potentials, providing ecological insights into flavor differentiation and theoretical support for objective fermentation degree evaluation and quality control of Jiangxiangxing Baijiu production.

Fermentation↗

PubMed2024

PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis.

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

Proteomics↗